Investigating the Effects of Near-Streamflow Regions on Temperate Region Lake Ice
Bibliographic record
Abstract
This study uses a combination of modeling and fieldwork to investigate the relationship between stream outflows and lake ice in Central Ontario, by focusing on Clear and MacDonald Lakes in Haliburton Forest and Wild Life Reserve. A network of waterproof temperature sensors (HOBO pendants and tidbits) were submerged 1 – 4 m below the water level, and Reconyx outdoor digital cameras were installed around the outflows at both lakes. Results indicate thinner or no ice, and an earlier spring ice-off closer to the outflow regions. Incorporating an additional heat flux in the lake ice model to represent the near-streamflow heat sources, 9.5 Wm-2 for 2017 – 2018, and 20.5 Wm-2 for the 2018 – 2019, led to more accurate simulations of the lake outflow regions. Overall, results show that the near-streamflow region ice is unsafe for recreation most of the winter season, highlighting the need for accurate ice information and awareness for users.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".